An aberrant DNA methylation signature for predicting the prognosis of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy worldwide with a poor prognosis. DNA methylation is an epigenetic modification that plays a critical role in the etiology and pathogenesis of HNSCC. The current study aimed to develop a predictive methylation signature based on bio...

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Bibliographic Details
Published in:Cancer medicine (Malden, MA) MA), 2021-09, Vol.10 (17), p.5936-5947
Main Authors: Chen, Dayang, Wang, Mengmeng, Guo, Ying, Wu, Wei, Ji, Xiang, Dou, Xiaowen, Tang, Huamei, Zong, Zengyan, Zhang, Xiuming, Xiong, Dan
Format: Article
Language:English
Subjects:
Bioinformatics
Biomarkers
Cancer therapies
Clinical Cancer Research
Deoxyribonucleic acid
DNA
DNA methylation
DNA Methylation - genetics
Epigenetics
Etiology
Female
Gender
Gene expression
Genomes
Head & neck cancer
Head and neck carcinoma
HNSCC
Humans
Male
Malignancy
Medical prognosis
Medical records
Medical screening
Metastasis
Middle Aged
nomogram
Nomograms
Patients
Prognosis
Regression analysis
Risk groups
risk score
Software
Squamous cell carcinoma
Squamous Cell Carcinoma of Head and Neck - genetics
Statistical analysis
Survival analysis
Tumors
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Summary:Head and neck squamous cell carcinoma (HNSCC) is a common malignancy worldwide with a poor prognosis. DNA methylation is an epigenetic modification that plays a critical role in the etiology and pathogenesis of HNSCC. The current study aimed to develop a predictive methylation signature based on bioinformatics analysis to improve the prognosis and optimize therapeutic outcome in HNSCC. Clinical information and methylation sequencing data of patients with HNSCC were downloaded from The Cancer Genome Atlas database. The R package was used to identify differentially methylated genes (DMGs) between HNSCC and adjacent normal tissues. We identified 22 DMGs associated with 246 differentially methylated sites. Patients with HNSCC were classified into training and test groups. Cox regression analysis was used to build a risk score formula based on the five methylation sites (cg26428455, cg13754259, cg17421709, cg19229344, and cg11668749) in the training group. The Kaplan–Meier survival curves showed that the overall survival (OS) rates were significantly different between the high‐ and low‐risk groups sorted by the signature in the training group (median: 1.38 vs. 1.57 years, log‐rank test, p 
ISSN:2045-7634
2045-7634
DOI:10.1002/cam4.4142